Dispersed storage with coordinated execution and methods for use therewith

ABSTRACT

A dispersed storage and task (DST) processing unit receives an access request. An estimated processing load, associated with the access request, is determined. A processing resource is selected based on the estimated processing load. A coordinated execution schedule is determined for a plurality of DST execution units. The access request is assigned to the processing resource in accordance with the coordinated execution schedule.

CROSS REFERENCE TO RELATED PATENTS

This patent application is claiming priority under 35 USC §119(e) to aprovisionally filed patent application entitled OPTIMIZING DATA STORAGEIN A DISPERSED STORAGE NETWORK having a provisional filing date of Aug.29, 2013, and a provisional Ser. No. 61/871,649, which is incorporatedherein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network in accordance with the present invention;

FIG. 40B is a diagram of an embodiment of a storage file structure inaccordance with the present invention;

FIG. 40C is a flowchart illustrating an example of writing data inaccordance with the present invention;

FIG. 40D is a flowchart illustrating an example of accessing encodeddata slices in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 41B is a flowchart illustrating an example of accessing data inaccordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of scheduling an accessrequest in accordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of completing writing ofencoded data slices in accordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 44B is a flowchart illustrating an example of updating accesscontrol information in accordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adistributed storage and task execution unit in accordance with thepresent invention;

FIG. 45B is a flowchart illustrating an example of configuring adistributed storage and task unit in accordance with the presentinvention;

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 46B is a flowchart illustrating an example of securely receivingdata in accordance with the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 47B is a flowchart illustrating an example of balancing storageunit utilization in accordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention; and

FIG. 48B is a flowchart illustrating an example of adjusting data accessthroughput in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations include authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the first set of encoded data slices include errorcorrection data based on the first-third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—)1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—)2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—)3) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—)4, whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—)5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—)1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_(—)1_AA, and DS parameters of ⅗;SEG_(—)1; and SLC_(—)1. In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., ⅗ for the first data entry), segmentsecurity information (e.g., SEG_(—)1), per slice security information(e.g., SLC_(—)1), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of ⅗; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., ⅗ for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1_(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or any other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compareto ID errors (ordered after task 1_(—)4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of ⅗ for their decode threshold/pillar width; hence spanningthe memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words).

Task 1_(—)3 (e.g., translate) includes task execution information asbeing non-ordered (i.e., is independent), having DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate data partitions2_(—)1 through 2_(—)4 and having DT execution modules 1_(—)2, 2_(—)2,3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5 through 2_zto produce task 1_(—)3 intermediate results (R1-3, which is thetranslated data). In this example, the data partitions are grouped,where different sets of DT execution modules perform a distributedsub-task (or task) on each data partition group, which allows forfurther parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3 z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3 z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_(—)1 through R1-3_z) to produce task 3_(—)2 intermediate results(R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2_m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g.,1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_(—)4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabyte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network that includes the distributed storage and task (DST)client module 34 and the plurality of DST execution units 36 of FIG. 1.Each DST execution unit 36 includes a processing module 84 and a memory88. The memory 88 stores a plurality of storage files 1-S. Each storagefile stores encoded data slices. The system functions to access data inthe plurality of DST execution units 36. In an embodiment, a dispersedstorage and task (DST) processing unit 16 includes a client module 34,when operable within a computing device, that causes the computingdevice to perform the following method steps: selecting a slice lengthfor a data segment to be stored in the DSN; encoding the data segmentusing a dispersed storage error coding function to produce a set of dataslices in accordance with the slice length; selecting a storage filebased on the slice length; generating a storage file identifier (ID)that indicates the storage file; generating a set of DSN addressescorresponding to the set of data slices, wherein the set of DSNaddresses each include the storage file ID and a corresponding one of aplurality of offset identifiers (IDs); writing the set of data slices inaccordance with the set of DSN addresses; and updating a directory toassociate the set of DSN addresses with an identifier of the datasegment.

A first storage file can be selected when the slice length has a firstvalue and a second storage file is selected when the slice length has asecond value. The first storage file can be selected when the slicelength falls within a first range of values and a second storage file isselected when the slice length falls within a second range of values.The storage file can include a file header that includes the pluralityof offset identifiers and a corresponding plurality of slice locations.

Each of the plurality of data slices can be stored in the storage filewith the selected slice length at one of a plurality of slice locations.The slice length can be selected based on one or more of: a length ofthe data segment, a predetermination, a vault identifier, a data type ofthe data segment, or a storage utilization level. The selection of thestorage file can be further based on one or more of: a data type of thedata segment, a data owner of the data segment, a vault identifier, adata priority level of the data segment, or a preference of a DSNdevice.

The method described above in conjunction with a DST processing unit 16can alternatively be performed by other modules of a dispersed storagenetwork, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), cause the one or more computing devices to perform any or all ofthe method steps described above.

In an example of operation, the DST client module 34 receives a requestto access the data, such as access request 214 from DST client module34. The request to access the data includes at least one of a write datarequest and a read data request. When the request to access the dataincludes the write data request, the DST client module 34 encodes thedata using a dispersed storage error coding function associated with thedata to produce sets of encoded data slices. Each slice includes a slicelength number of bytes in accordance with the dispersed storage errorcoding function. The DST client module 34 determines the dispersedstorage coding function based on the data by at least one of a vaultidentifier (ID), a lookup based on the vault ID, a requesting entity ID,a predetermination, a data type indicator, a data size indicator, and arequest.

Having produced the sets of encoded data slices, the DST client module34 generates a storage file ID 204 based on a commonality factor of thesets of encoded data slices and other sets of encoded data slices storedwithin the plurality of DST execution units 36. The commonality factorincludes at least one of a slice length range, a data type, a datalength, a data owner ID, and an association with a common vault ID. Forexample, the DST client module 34 generates a storage file ID 214associated with a first storage file when slice lengths of the sets ofencoded data slices fall within a range of 1 to 2 MB slice lengthsassociated with the storage file 1 and the storage file ID is available(e.g., not utilized for storage of other data). As another example, theDST client module 34 generates another storage file ID 214 associatedwith a second storage file when the slice lengths of the sets of encodeddata slices fall within another range of 15 to 30 MB slice lengthsassociated with the storage file 2 and the other storage file ID 214 isavailable.

Having selected the storage file ID 214, the DST client module 34generates sets of unique DSN addresses 202 for the sets of encoded dataslices based on the storage file ID 214. Each DSN address 202 includesthe storage file ID 204 (e.g., common for all sets of encoded dataslices) and an offset ID 206, where the offset ID 206 is unique for eachencoded data slice. For example, the offset ID 206 can be associatedwith each set of encoded data slices. As another example, the offset ID206 can be associated with a magnitude of a number of encoded dataslices of a group of associated encoded data slices. The DST clientmodule 34 generates sets of write access requests, where each writeaccess request includes an access type 208 (e.g., an access type fieldmay include indicators for other access types including reading,listing, and deleting for other access requests), a corresponding DSNaddress 202, and a corresponding encoded data slice 212. For example,the DST client module 34 generates the access type 208 to indicate awrite slice request. The DST client module 34 sends the sets of writeaccess requests to a set of DST execution units 36 of the plurality ofDST execution units 36. The DST client module 34 updates at least one ofa DSN directory and a dispersed hierarchical index to associate the setsof DSN addresses and an identifier of the data to facilitate subsequentdata retrieval. The method of operation of the DST client module 34,including several optional functions and features, is discussed ingreater detail with reference to FIG. 40C. The method of operation ofthe DST execution unit 36, including several optional functions andfeatures, is discussed in greater detail with reference to FIGS. 40B and40D.

FIG. 40B is a diagram of an embodiment of a storage file structure tofacilitate storage of encoded data slices (232, 236, 240, 244 . . . )within an associated storage file 220, where a dispersed storage network(DSN) address includes a storage file identifier (ID) and an offset ID226 utilized in selection of the storage file 220 and a storagelocation, such as slice location 228 within the storage file 220. Thestorage file 220 includes a file header 224, a plurality of encoded dataslices (232, 236, 240, 244 . . . ), and a plurality of slice lengths(230, 234, 238, 242 . . . ) associated with the plurality of encodeddata slices (232, 236, 240, 244 . . . ). Alternatively, or in additionto, the storage file 220 may also include a plurality of integrityvalues associated with the plurality of encoded data slices (232, 236,240, 244 . . . ). The file header 224 and the plurality of associatedencoded data slices (232, 236, 240, 244 . . . ), and slice lengths (230,234, 238, 242 . . . ) are stored at corresponding ones of the filelocations 222 within the storage file 220. The file locations 222include either an absolute address within the storage file or an offsetwithin the storage file. For example, the file header 224 can be storedat an offset of zero and a first associated encoded data slice 232 andslice length 230 can be stored at an offset with a value of “0200”.

The file header 224 includes pairings of an offset ID entry 226 and aslice location entry 228 for a set of 1-N offset IDs 226 associated withthe storage file 220. For each offset ID 226, the file header 224 isutilized to indicate at what file location 222 an encoded data slice(232, 236, 240, 244 . . . ) and associated slice length (230, 234, 238,242, . . . ) are stored. For example, the first associated encoded dataslice 232 and slice length 230 are associated with offset ID 1 and arestored at a slice location 228 of the file location 222 with a value of“0200”. As another example, a second associated encoded data slice236/slice length 234 are associated with offset ID 2 and are stored at aslice location 228 of file location 222 with a value of “20FF”.

When an association does not exist between an available offset ID 226and a encoded data slice and slice length pairing, an available markercan be included in the slice location field 228 (e.g., −1). As such, anassociated DSN address that includes a storage file ID associated withthe storage file 220 and the available offset number may be assignedwhen writing a new encoded data slice to the storage file 220.

In an example of writing an encoded data slice (232, 236, 240 or 244 . .. ) to the storage file 220, the storage file ID of the DSN address isutilized to access the storage file 220 associated with the storage fileID of a write request. The file header 224 is retrieved from the storagefile 220. An available storage/slice location 228 within the storagefile 220 is identified. For example, a storage location availabilitytable is accessed to identify a storage location that includessufficient space to store the encoded data slice (232, 236, 240 or 244 .. . ). As another example, the file header 224 is utilized and slicelengths (230, 234, 238, 242 . . . ) are gathered from slice locations228 to identify the available storage location. With the availablestorage location identified, the file header 224 is updated to includethe storage location as the sliced location 228 associated with thecorresponding offset ID 226 of the DSN address. The encoded data sliceand a slice length of encoded data slice are stored at the storagelocation 228 that is selected.

The file header 224 may be utilized when reading an encoded data slice(232, 236, 240 or 244 . . . ) from the storage file 220. In an exampleof reading the encoded data slice (232, 236, 240 or 244 . . . ), thefile header 224 is retrieved from the storage file 220 based on thestorage file ID of the DSN address. The slice location 228 is extractedfrom the file header 224 based on the offset ID 226 of the DSN address.The slice location 228 is accessed to retrieve the slice length (230,234, 238 or 242 . . . ). The encoded data slice (232, 236, 240 or 244 .. . ) is retrieved from the storage file 220 based on the slice location228 and the slice length (230, 234, 238 or 242 . . . ) (e.g., recoveredat an offset just beyond a field that stores the slice length entry).

The file header 224 is updated when deleting an encoded data slice (230,234, 238 or 242 . . . ). In an example of deleting the encoded dataslice (230, 234, 238 or 242 . . . ), a delete slice access requestincludes the DSN address. The storage file 220 is accessed based on thestorage file ID of the DSN address. The file header 224 is extractedfrom the storage file 220. The file header 224 is updated to indicatethat the offset ID 226 of the DSN address is available. For example, theslice location field 228 associated with the offset ID 226 is marked toindicate that there is no associated encoded data slice (230, 234, 238or 242 . . . ). The storage location availability table is updated toindicate that the storage location previously associated with theencoded data slice is available when the storage location availabilitytable is utilized.

Upon deletion of the encoded data slice (230, 234, 238 or 242 . . . ) orat any other time, a determination is made whether to compress thestorage file 220. When compressing the storage file 220, a remainingplurality of encoded data slices (230, 234, 238 or 242 . . . ) arepacked together at a plurality of the storage locations 228. The fileheader 224 is updated to include the plurality of new storage locations228 with corresponding offset IDs 226 associated with the plurality ofencoded data slices (230, 234, 238 or 242 . . . ).

FIG. 40C is a flowchart illustrating an example of writing data. Themethod includes step 250 where a processing module (e.g., of adistributed storage and task (DST) client module) selects a slice lengthfor data to be stored in a dispersed storage network (DSN). Theselection may be based on one or more of length of the data, apredetermination, a vault identifier (ID), a data type indicator, and astorage utilization level. For example, the processing module selects asmaller than average slice length when the data is smaller than average.As another example, the processing module selects a smaller than averageslice length when the storage utilization level is higher than a maximumstorage utilization threshold level.

The method continues at step 252 where the processing module encodes thedata using a dispersed storage error coding function to produce sets ofencoded data slices in accordance with the slice length. The methodcontinues at step 254 where the processing module generates a storagefile ID based on commonality attributes of the data. The commonalityattributes include one or more of the slice length, the data type, adata owner, a vault ID, a data priority level, and a DST execution unitset preference. The generating can include generating the storage fileID to be within a storage file ID range of storage file IDs associatedwith the commonality attributes. For example, the processing modulegenerates the storage file ID to be associated with a first range forencoded data slices with less than average slice lengths. As anotherexample, the processing module generates the storage file ID to beassociated with a second range for encoded data slices with averageslice lengths. As yet another example, the processing module generatesthe storage file ID to be associated with a third range for encoded dataslices with greater than average slice lengths.

The method continues at step 256 where the processing module generatessets of unique DSN addresses for the sets of encoded data slices, whereeach DSN address includes the storage file ID and an offset ID. Theoffset ID can be unique for at least one of each set of encoded dataslices and a grouping of associated encoded data slices. The methodcontinues at step 258 where the processing module issues a set of writeslice access requests to a set of storage units that includes the setsof encoded data slices and the sets of unique DSN addresses. The methodcontinues at step 260 where the processing module updates a DSNdirectory to associate the sets of unique DSN addresses with a dataidentifier of the data.

FIG. 40D is a flowchart illustrating an example of accessing encodeddata slices. The method includes step 270 where a processing module(e.g., of a distributed storage and task (DST) client module), for awrite sequence, accesses a storage file corresponding to a storage fileidentifier (ID) of a write access request to retrieve a file header. Forexample, the processing module performs a storage file location lookupbased on the storage file ID to retrieve the storage file and extractthe file header from the storage file. The method continues at step 272where the processing module identifies an available storage locationwithin the storage file based on a slice length of an encoded data slicefor storage. The identifying can include analyzing the file header andslice lengths at storage locations referenced by the file header toidentify available storage space with sufficient capacity to store theencoded data slice for storage.

The method continues at step 274 where the processing module updates thefile header to include the storage location for a corresponding offsetID (e.g., from the write access request) of the encoded data slice forstorage. The method continues at step 276 where the processing modulestores the slice length and the encoded data slice at the identifiedstorage location. Alternatively, or in addition to, the processingmodule stores an integrity value (e.g., received and/or generated) ofthe encoded data slice with the slice length and encoded data slice atthe identified storage location.

For a read access sequence, the method continues at step 278 where theprocessing module accesses the storage file corresponding to the storagefile ID of a read access request to retrieve the file header. The methodcontinues at step 280 where the processing module identifies the storagelocation within the storage file based on an offset ID of the readrequest. The identifying can include utilizing the offset ID to accessthe storage location within the file header. The method continues atstep 282 where the processing module accesses the storage locationwithin the storage file to retrieve the slice length of the encoded dataslice. For example, the processing module can add the storage locationto a beginning address of the storage file and the storage location isan offset or directly accesses the storage location when the storagelocation is an absolute address. The method continues at step 284 wherethe processing module extracts a slice length number of bytes from thestorage file from a slice storage field of the storage location toproduce the encoded data slice.

For a delete access sequence, the method continues at step 286 where theprocessing module receives a delete slice access request that includesthe storage file ID and the offset ID. The method continues at step 288where the processing module accesses the storage file corresponding tothe storage file ID to retrieve the file header. The method continues atstep 290 where the processing module updates the file header to indicatethat the encoded data slice associated with the offset ID has beendeleted. For example, the processing module updates the file header toindicate that the offset ID is available (e.g., replaces a storagelocation with an available marker).

The method continues at step 292 where the processing module determineswhether to compress the storage file. The determining may be based onone or more of interpreting a schedule, detecting that an amount ofavailable contiguous storage space is less than a low space thresholdlevel, detecting that a memory utilization level is greater than amaximum utilization threshold level, detecting deletion of encoded dataslice, and/or receiving a request. When compressing the storage file,the method continues at step 294 where the processing module packs aplurality of encoded data slices associated with a plurality of offsetIDs together in the storage file at a new plurality of storagelocations. The packing may include temporarily buffering at least someof the plurality of encoded data slices while moving encoded data slicesfrom previous storage locations to the new plurality of storagelocations. Some level of overlap may occur between the previous storagelocations in the new plurality of storage locations. For instance,encoded data slices been stored at a same storage location and a secondencoded data slice being stored at a previous storage location of afirst encoded data slice. The method continues at step 296 where theprocessing module updates the file header to associate the plurality ofoffset IDs with the new plurality of storage locations.

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network that includes the distributed storage and task(DST) client module 34 and the plurality of DST execution units 36 ofFIG. 1 (e.g., a set of DST execution units 1-n). Each DST execution unit36 includes a processing module 84 and a plurality of memories. Eachmemory stores a plurality of encoded data slices (e.g., 1-M, 1-N, 1-P,etc.). The system functions to access data in the plurality of DSTexecution units.

In an embodiment, the dispersed storage and task (DST) processing unit16 includes at least one module, such as DST client module 34, whenoperable within a computing device, that causes the computing device toperform the following method steps: receiving a data access requestcorresponding to a data segment; obtaining range availabilityinformation for a plurality of DST execution units of the DST network;selecting a subset of the plurality of DST execution units based on therange availability information and a threshold number corresponding tothe data access request; and generating execution unit access requeststo the subset of the plurality of DST execution units corresponding to aplurality of slices of the data segment, wherein the execution unitaccess requests include address information that is based on the rangeavailability information.

The threshold number can correspond to a read threshold number when thedata access request includes a read request and the threshold number cancorrespond to a write threshold number when the data access requestincludes a write request and wherein the read threshold number is lessthan the write threshold number. The range availability information forthe plurality of DST execution units can include at least one of: ahistorical record of range availability for the plurality of DSTexecution units, a range availability response to a query to at leastone of the plurality of DST execution units, an error messagecorresponding to at least one of the plurality of DST execution units,and/or a test of range availability of the plurality of DST executionunits.

Each of the plurality of DST execution units can include a correspondingrange of DST addresses and the address information can be generated tocorrespond to the range of DST addresses of the subset of the pluralityof DST execution units. At least one of DST execution units can includea plurality of memory subranges, and the range availability informationcan identify at least one of the plurality of subranges—wherein theaddress information is determined based on the at least one of theplurality of subranges.

The process of selecting the subset of the plurality of DST executionunits can include including ones of the DST execution units with rangeavailability in the subset of the plurality of DST execution units. Theprocess of selecting the subset of the plurality of DST execution unitscan further be based on a determination, for the subset of the pluralityof DST execution units, at least one of, a current level of activity, apredicted level of input/output activity, or a predicted level of slicerebuilding.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), cause the one or more computing devices to perform any or all ofthe method steps described above.

In an example of operation, the DST client module 34 assigns a dispersedstorage network (DSN) address range to each of the DST execution units.Alternatively, a distributed storage and task network (DSTN) managingunit assigns the DSN address range. As such, encoded data slices with aDSN address that fall within the DSN address range are directed to theassociated DST execution unit. For example, an encoded data sliceassociated with a range one DSN address is directed to a first DSTexecution unit (e.g., DST execution unit range 1). At least one of theprocessing module 84 and the DST client module 34 assigns a set of 1-RDSN address sub-ranges within an associated DSN address range of a DSTexecution unit, where each DSN address sub-ranges associated with amemory of the plurality of memories. For example, the processing module84 assigns a first DSN address sub-range to a first memory (e.g., memorysub-range 1). As such, encoded data slices 1-M associated with the firstDSN address sub-range are stored within the first memory.

In an example of accessing data, the DST client module 34 generates orreceives a data access request 300. The DST client module 34 obtainsrange availability information 302 associated with memories of the DSTexecution units. The range availability information can include one ormore of, by a DSN address sub-range, a performance level, a reliabilitylevel, and/or an availability level. The obtaining can include at leastone of issuing a range availability request, interpreting an errormessage, accessing a historical record, or receiving the rangeavailability information.

Having obtained the range availability information 302, the DST clientmodule 34 generates addressing information based on the data accessrequest 300 and the range availability information 302. For example,when the data access request 302 is a write data access request, the DSTclient module 34 selects a DSN address within a DSN address sub-rangeassociated with most favorable range availability information 302 (e.g.,more favorable performance than others). As another example, when thedata access request 300 is a read data access request, the DST clientmodule 34 retrieves the DSN address from a DSN directory based on a dataID of the data access request.

The DST client module 34 generates a threshold number of access requests300 based on the range availability information 302. The access request300 can include the addressing information. For example, the DST clientmodule 34 selects a subset of DST execution units based on the rangeavailability information 302 (e.g., more favorable performance). The DSTclient module 34 sends the threshold number of access requests 300 to anassociated threshold number of DST execution units.

FIG. 41B is a flowchart illustrating an example of accessing data. Themethod includes step 310 where a processing module (e.g., of adistributed storage and task (DST) client module) receives a data accessrequest (e.g. read, write). The method continues at step 312 where theprocessing module obtains range availability information for one or moresets of DST execution units. For example, the processing module performsa range availability performance test to acquire performance informationas the availability information. The method continues at step 314 wherethe processing module generates addressing information based on the dataaccess request and range availability information.

The method continues at step 316 where the processing module generatesone or more sets of a threshold number of access requests based on therange availability information. For example, when the data accessrequest is a read access request, the processing module generates a readthreshold number of read slice access requests. As another example, whenthe data access request is a write access request, the processing modulegenerates a write threshold number of write slice access requests. Thegenerating can include selecting the threshold number of addressingsub-ranges associated with favorable range availability information. Forexample, the processing module selects addressing sub-ranges associatedwith a least amount of pending access requests. As another example, theprocessing module selects addressing sub-ranges associated with a leastamount of pending encoded data slice rebuilding requests.

The method continues at step 318 where the processing module sends theone or more sets of the threshold number of access requests to anassociated threshold number of DST execution units. Sending the accessrequests can include identifying the threshold number of DST executionunits associated with the selected addressing sub-ranges.

FIG. 42A is a schematic block diagram of another embodiment of adispersed storage network that includes the distributed storage and task(DST) client module 34 and the plurality of DST execution units 36 ofFIG. 1 (e.g., a set of DST execution units 1-n). Each DST execution unit36 includes a processing module 84 and a memory 88. Each memory 88stores a plurality of encoded data slices (326, 328 . . . ). The systemfunctions to prioritize access of data in the plurality of DST executionunits.

In an embodiment, the dispersed storage and task (DST) processing unit16 includes at least one module, when operable within a computingdevice, that causes the computing device to perform the following methodsteps: receiving an access request; determining an estimated processingload associated with the access request; selecting a processing resourcebased on the estimated processing load; determining a coordinatedexecution schedule for a plurality of DST execution units; and assigningthe access request to the processing resource in accordance with thecoordinated execution schedule. In addition, the method can furtherinclude: detecting an execution deviation in the coordinated executionschedule; and updating the coordinated execution schedule in response tothe execution deviation.

The estimated processing load can be determined based on at least oneof: an access type corresponding to the access request, or a quantity ofdata slices associated with the access request. The processing resourcecan be selected from a plurality of processing resources, based on acapability of the processing resource.

The coordinated execution schedule can be determined based on at leastone of: an execution status associated with one or more current accessrequests, or a number of access requests in queue. The coordinatedexecution schedule can also be determined to coordinate commencement ofthe access request across at least a subset of the plurality of DSTexecution units. The coordinated execution schedule can also bedetermined to coordinate commencement of the access request across atleast a subset of the plurality of DST execution units based on anestimated completion time of one or more prior access requests.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), cause the one or more computing devices to perform any or all ofthe method steps described above.

In an example of operation, the DST client module 34 sends an accessrequest 320 to a DST execution unit 36. The access request 320 isassociated with one or more encoded data slices and a common task, wherethe common task includes at least one access type including reading,writing, deleting, and listing. The processing module 84 of the DSTexecution unit 36 receives the access request 320. The processing module84 determines an estimated processing load to service the access requestbased on one or more of the access type and quantity of encoded dataslices of the access request 320. The processing module 84 selects aprocessing resource for the access request based on the estimatedprocessing load and capability of the processing resource. For example,the processing module 84 selects the memory 88 and a CPU of theprocessing module 84.

Having selected the processing resource, the processing module 84determines an execution schedule for the access request based on statusof executing a current access request and other previously queued accessrequests assigned to processing resources of the set of DST executionunits. The processing of the access request is scheduled to commence atan estimated time of completion of all current and pending accessrequests associated with the processing resource. The estimated time ofcompletion is similar across the set of DST execution units. Theprocessing module 84 exchanges execution schedule information 324 withother DST execution units 36, where the other DST execution units 36receive associated access requests 320. The processing module 84 assignsaccess request 320 to the selected processing resource in accordancewith the execution schedule to facilitate execution of the accessrequest. Upon completion of the access request, the processing module 84issues an access response 322 to the DST client module 34 that includesresults of the access request (e.g., status of a write the encoded datarequest, an encoded data slice from a read request, a status from adelete encoded data slice request).

FIG. 42B is a flowchart illustrating an example of scheduling an accessrequest. The method includes step 330 where a processing module (e.g.,of a distributed storage and task (DST) execution unit) receives anaccess request (e.g., read, write, delete, list, etc.). The methodcontinues at step 332 where the processing module determines anestimated processing load of the access request. The determiningincludes at least one of performing a lookup based on an access type ofthe read access request, initiating a query, receiving processing loadinformation, and/or accessing a historical record. The method continuesat step 334 where the processing module selects a processing resourcebased on the estimated processing load. The selecting includesidentifying the processing resource that as processing availability andis capable of executing the access request.

The method continues at step 336 where the processing module determinesa coordinated execution schedule for the access request, where theexecution schedule is coordinated with a set of DST execution units. Thedetermining includes, when the access request is one of a thresholdnumber of access requests sent to a threshold number of DST executionunits, aligning a start time for execution of the access request withthe other DST execution units based on one or more of an estimated timeof availability of the selected processing resource and availability ofthe other DST execution units to initiate execution of correspondingaccess requests. The processing module exchanges execution scheduleinformation (e.g., current request processing, pending requestprocessing, estimated time of availability of one or more processingresources) with the other DST execution units to facilitate thedetermination of the coordinated execution schedule for the accessrequest.

The method continues at step 338 where a processing module assigns theaccess request to the selected processing resource in accordance withthe coordinated execution schedule. The assigning includes schedulingthe selected processing resource to execute the access request at thestart time. The method continues at step 340 where the processingmodule, when detecting an execution deviation, updates the coordinatedexecution schedule. The updating includes detecting the executiondeviation by exchanging execution schedule information with thethreshold number of DST execution units and indicating the executiondeviation when one or more DST execution units indicate that processingof an associated access request is behind schedule in relation to thecoordinated execution schedule. The updating further includes realigningselection of processing resources to improve adherence to the updatedcoordinated execution schedule.

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network that includes the DST client module 34 and aset of DST execution units 1-n of FIG. 1. The DST client module 34includes a slice cache memory 350. The system functions to store sets ofencoded data slices in the set of DST execution units 1-n.

In an example of operation, in a first timeframe, the DST client moduleissues a set of write slice requests 1-n to store a set of encoded dataslices A in the set of DST execution units 1-n. When receiving at leasta write threshold number of favorable write slice responses (e.g.,acknowledging storage of an associated read threshold number of encodeddata slices of the set of encoded data slices), the DST client module 34identifies any encoded data slices not associated with a storageacknowledgment. For instance, the DST client module 34 does not receivea write slice response for encoded data slice 3.

The DST client module 34 stores the encoded data slices not associatedwith the storage acknowledgment (e.g., without write confirmation) inthe slice cache 350. For example, the DST client module 34 storesencoded data slice 3_A in a cache memory. The DST client module 34overwrites an oldest previously stored encoded data slice in the slicecache 350 when the slice cache 350 is full. The DST client module 34determines whether to resend an encoded data slice without writeconfirmation to associated DST execution unit based on one or more ofreceiving a DST execution unit availability indicator, interpreting aresend schedule, receiving an error message, receiving an access requestresponse, receiving a resend request that request resending encoded dataslices without write confirmation, and receiving a rebuilding request.For example, the DST client module 34 determines to resend encoded dataslice 3_A when DST execution unit 3 issues a DST execution unit 3available message.

When determining to resend the encoded data slice without writeconfirmation, the DST client module 34 resends the encoded data slicewithout write confirmation to the associated DST execution unit. Forexample, the DST client module 34 resends encoded data slice 3_A to theDST execution unit 3. When receiving a favorable write slice response,the DST client module 34 deletes the encoded data slice without writeconfirmation from the slice cache. For example, the DST client module 34receives a encoded data slice 3 write slice response (e.g., a favorableacknowledgment) and deletes encoded data slice 3_A from the slice cache350.

FIG. 43B is a flowchart illustrating an example of completing writing ofencoded data slices. The method includes step 360 where a processingmodule (e.g., of a distributed storage and task (DST) client module)issues a set of write slice requests to a set of storage units. Theissuing includes generating and sending at least a write thresholdnumber of write slice requests, where each request includes an encodeddata slice. When receiving at least a write threshold number offavorable write slice responses, the method continues at step 362 wherethe processing module identifies one or more encoded data slices withoutstorage confirmation. The identifying includes receiving write sliceresponses, determining whether each write slice response indicatesfavorable writing, and detecting whether no write slice response hasbeen received for an encoded data slice within a response timeframe.

The method continues at step 364 where the processing module temporarilystores the one or more encoded data slices without storage confirmationin a local memory (e.g., a cache memory). The storing includesoverwriting an oldest encoded data slice previously stored in the localmemory when the local memory is full. The method continues at step 366where the processing module determines to resend a write slice requestfor an encoded data slice without storage confirmation. The determiningincludes at least one of receiving an availability indicator,interpreting a resend schedule, receiving an error message, receiving anaccess request response, receiving a resend request, and receiving arebuilding request.

When resending the write slice request, the method continues at step 368where the processing module resends the write slice request thatincludes the encoded data slice without storage confirmation. Forexample, the processing module retrieves the encoded data slice withoutstorage confirmation from the local memory and outputs the encoded dataslice to an associated storage unit. When receiving a favorable writeslice response, the method continues at step 370 where the processingmodule deletes the encoded data slice without storage confirmation fromthe local memory. The deleting includes receiving a write slice responseand detecting favorable writing within a response timeframe from theresending of a write slice request.

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed computingsystem 10 of FIG. 1. The distributed storage and task network (DSTN)managing unit 18 generates a dispersed storage network (DSN) accesswhitelist. The generating is based on one or more of a templatewhitelist, a manager input, detecting devices of the distributedcomputing system 10, and receiving vault association information. Thevault association information associates devices of the distributedcomputing system 10. For example, a first distributed storage and task(DST) processing unit 16 is associated with a first set of DST executionunits 36 for a first vault and a second distributed storage and task(DST) processing unit 16 is associated with a second set of DSTexecution units 36 for a second vault. Each association indicates whichdevices are authorized to communicate with each other to co-executeservices supported by the distributed computing system 10. Such servicesincludes one or more of writing data, reading data, deleting data,listing data, rebuilding data, and managing configuration parameters ofthe system.

The DSN access whitelist 380 includes a plurality of sets of entrieswhere each set of entries includes a first entry for a serviceidentifier (ID) field 390, a second entry for a device ID field 392, athird entry for a initiate to device IDs field 394, and a fourth entryfor a received from devices IDs field 396. Entries of the service IDfield 390 indicate a service type of the services supported by thesystem. Entries of the device ID field 392 indicate an identifierassociated with one of the devices of the system (e.g., a universallyunique identifier associated with one or more of the user device 12, theDST processing unit 16, etc.). Entries of the initiate to device IDsfield 394 indicate one or more allowable device IDs to be targeted foran associated service type. Entries of the received from device IDsfield 396 indicate one or more allowable device IDs to accept requestsfrom with regards to the associated service type.

With the whitelist 380 generated, the DSTN managing unit 18 distributesthe DSN access whitelist 380 to each device of the system. For example,from time to time, the DSTN managing unit 18 publishes registryinformation to one or more of the devices of the system, where theregistry information includes the DSN access whitelist 380. The methodto generate and distribute the DSN access whitelist is discussed ingreater detail with reference to FIG. 44B.

FIG. 44B is a flowchart illustrating an example of updating accesscontrol information. The method includes step 400 where a processingmodule (e.g., of a distributed storage and task network (DSTN) managingunit) obtains dispersed storage network (DSN) physical configurationinformation for a plurality of devices of the DSN. The DSN physicalconfiguration information includes one or more of identities of thedevices, device types of the devices, and one or more network addressesfor each device. The obtaining includes at least one of initiating aquery, receiving a response, receiving manufacturing device information,interpreting a manager input, and receiving a template. The methodcontinues at step 402 where the processing module determines DSN logicalconfiguration information for the plurality of devices. The DSN logicalconfiguration information includes one or more of identities ofprocesses supported, process types, and assignments of processes to adevice. The determining includes matching capabilities of a physicaldevice to required processes, interpreting a manager input, receiving atemplate, performing a test, initiating a query, and receiving a queryresponse.

The method continues at step 404 where the processing module obtains aDSN access whitelist template. The DSN access whitelist templateincludes typical entries for a DSN access whitelist (e.g., typicalservice initiators, typical service receivers by service type and devicetype). The obtaining includes at least one of receiving a manufacturingtemplate, obtaining a previous template, receiving a manager input thatincludes the template, and generating the template based on the DSNphysical configuration information and the DSN logical configurationinformation.

The method continues at step 406 where the processing module generates aDSN access whitelist based on the DSN access whitelist template, the DSNphysical configuration information, and the DSN logical configurationinformation. The generating includes modifying the DSN access whitelisttemplate in accordance with the DSN physical configuration informationand the DSN logical configuration information. For example, theprocessing module, for each service supported by the DSN, enable onlythose devices required to send service requests of the service and toenable only those devices required to receive the service requests ofthe service. For instance, the processing module modifies the DSN accesswhitelist template to associate a set of distributed storage and task(DST) execution units with a DST processing unit where the DSTprocessing unit is authorized to request data access services and theset of DST execution units are authorized to receive the requested dataaccess services. In another instance, the processing module modifies theDSN access whitelist to enable the set of DST execution units toinitiate and share encoded data slice rebuilding service requestsbetween DST execution units. In yet another instance, the processingmodule modifies the DSN access whitelist to enable the DSTN managingunit to initiate simple network management protocol polling requests andcanned registry publishing service requests and for all other devices toreceive and process the simple network management protocol pollingrequests and the canned registry publishing service requests.

The method continues at step 408 where the processing module publishesthe DSN access whitelist to the plurality devices of the DSN. Forexample, the processing module outputs registry information to theplurality devices, where the registry information includes the DSNaccess whitelist. The method continues at step 410 where the processingmodule determines whether the DSN access whitelist is to be updated. Thedetermining includes at least one of interpreting an updating schedule,detecting a change in the DSN physical configuration information, anddetecting a change in the DSN logical configuration information.

When updating the DSN access whitelist, the method continues at step 412where the processing module updates the DSN access whitelist inaccordance with one or more of updated DSN physical configurationinformation and updated DSN logical configuration information. Theupdating includes determining the updated DSN physical configurationinformation, determining the updated DSN logical configurationinformation, and regenerating the DSN access whitelist based on theupdated DSN physical configuration information and the updated DSNlogical configuration information. The updating further includesrepublishing the updated DSN access whitelist to the plurality ofdevices of the DSN.

FIG. 45A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit 36 of FIG. 11. The DSTexecution unit 36 includes a variety of devices including an interface169, the memory 88, the controller 86, a plurality of distributed task(DT) execution modules 90, and a plurality of DST client modules 34. TheDST execution unit 36 functions to configure the variety of devices andto utilize the variety of configured devices to process partial taskrequests 98 and to process encoded data slice access requests (e.g.,receiving slices 96 for storage and retrieving slices 100).

In an example of configuring a variety of devices, the controller 86obtains status of the variety of devices of the DST execution unit 36,including the memory 88, the plurality of DT execution modules 90, andthe plurality of DST client modules 34. The obtaining includes one ormore of issuing a memory control message 174 to the memory 88, issuing atask control message 420 to the plurality of DT execution modules 90,issuing a DST control message 422 to the plurality of DST client modules34, receiving memory control information 174 from the memory 88 thatincludes memory status, receiving a task control message 420 from one ormore of the DT execution modules 90 that includes DT execution modulestatus, and receiving a DST control message from one or more of the DSTclient modules 34 that includes a DST client module status. The statusincludes one or more of processing utilization level information, memoryutilization level information, garbage collection logs, errorinformation, number of available computing cores, central processingunit (CPU) speed, actual task processing throughput levels, and pendingactivity information.

With the status of the devices obtained, the controller 86 generates astatus score based on the status of the devices. The status scoreincludes one or more of a memory score and a task execution score. Forexample, the controller generates a higher than average memory scorewhen the status indicates that a greater than average amount of storagespace of the memory 88 is available. As another example, the controllergenerates a lower than average task execution score when the statusindicates that the task processing throughput level is lower thanaverage. With the status score generated, the controller 86 determinesconfiguration information for the devices based on the status score. Forexample, the controller 86 increases a default cache memory size,increases a number of concurrent connections, increases memory availableto tasks, and increases a number of cached nodes of a dispersedhierarchical index when the memory score is higher than an averagememory score. As another example, the controller 86 increases a numberof rebuilding threads, increases frequency of rebuilding scanning, andincreases a number of distributor processing tasks when the taskexecution score is greater than an average task execution score. As yetanother example, the controller 86 turns off distributed processingtasks when the task execution score is lower than the average taskexecution score. As is still further example, the controller 86 disablesstorage of foster encoded data slices when the memory score is lowerthan the average memory score.

With the configuration information determined, the controller 86activates the configuration information with the devices of the DSTexecution unit 36. For example, the controller 86 issues the memorycontrol 174, the task control 420, and the DST control 422 to includethe configuration information.

In an example of utilizing the variety of configured devices, thecontroller 86 receives a request via the interface 169, where therequest includes at least one of a slice processing request and apartial task 98. The controller 86 identifies a resource type based onthe request (e.g., a DT execution module type for the partial task 98and a DST client module type for the slice processing request). Thecontroller 86 determines whether the resource type is available based onthe status. When the resource type is available, the controller 86selects a particular resource for assignment of the request. Forexample, the controller 86 identifies a third DST client module 34 thatis most available for the request when the request is the sliceprocessing request. As another example, the controller 86 selects afourth DT execution module 90 when the fourth DT execution module 90 isassociated with processing resources capable of executing the partialtask 98 when the request is the partial task 98. The controller 86assigns the request to the selected resource. The assigning includes atleast one of outputting an assignment task control message to anassigned DT execution module 90 and outputting an assignment DST controlmessage to the assigned DST client module. When the resource type is notavailable, the controller 86 may issue an error response via theinterface 169 to a requesting entity and/or to a managing unit.

The assigned DT execution module 90 executes the assigned partial task98 to produce partial results 102. Alternatively, or in addition to, theassigned DT execution module 90 facilitates the memory 88 to retrieveslices 96 and to output results 104. The assigned a DST client module 34executes the slice processing request to facilitate producing at leastone of sub-slice groupings 170 and sub-partial partial tasks 172.Alternatively, or in addition to, the DST client module 34 mayfacilitate the memory 88 to provide slices 100 and/or two receivesslices 96 for further slice processing.

The controller 86 may regenerate the status score to produce an updatedstatus score and updated configuration information based on theutilization of the variety of configured devices. In an example of theregenerating, the controller 86 determines whether to update theconfiguration information based on deviations of the updated statusscore. The determining includes updating the status score to produce theupdated status score and indicating to update the configurationinformation when the comparison of the updated status score and thestatus score is unfavorable (e.g., the scores are different by more thana deviation threshold level). When updating the configurationinformation, the controller 86 updates the configuration informationbased on the updated status scoring. The controller 86 activates theupdated configuration information with the devices of the DST executionunit 36.

FIG. 45B is a flowchart illustrating an example of configuring adistributed storage and task unit. The method includes step 430 where aprocessing module (e.g., of a controller of a distributed storage andtask (DST) execution unit) obtains status of a plurality of resources ofthe DST execution unit. The obtaining includes at least one ofinitiating a query, receiving a query response, performing a lookup,accessing a historical record, and interpreting a received errormessage. The method continues at step 432 where the processing modulegenerates a status score based on the status. The generating includesgenerating a memory score and a task execution score based on the status(e.g., a weighted scoring amongst a plurality of status factors).

The method continues at step 434 where the processing module determinesconfiguration information for the plurality of resources based on thestatus score. The determining includes determining processingconfiguration based on the task execution score and determining memoryconfiguration based on the memory score. The method continues at step436 where the processing module activates the plurality of resources inaccordance with the configuration information. For example, theprocessing module issues the configuration information to the pluralityof resources.

The method continues at step 438 where the processing module determineswhether to update the configuration information. The determiningincludes at least one of interpreting a configuration informationupdating schedule, receiving an error message, receiving a managerinput, and detecting a deviation of the status. When updating theconfiguration information, the method continues at step 440 where theprocessing module updates the configuration information based on updatedstatus scoring. The updating includes re-obtaining the status of theplurality of resources, regenerating the status score, andre-determining the configuration information to produce updatedconfiguration information. The method continues at step 442 where theprocessing module reactivates the plurality of resources in accordancewith the updated configuration information. The reactivating includesreissuing the updated configuration information to the plurality ofresources.

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network that includes the distributed storage and task(DST) client module 34 and a set of DST execution units 1-n of FIG. 1.The DST client module 34 includes the inbound DST processing 82 of FIG.3, a processing module 450, and an encryption module 464. The systemfunctions to securely provide data recovered from the set of DSTexecution units 1-n. In an example of operation, the processing module450 receives a secure data request 452. The secure data request 452includes one or more of a data identifier (ID) 456 of the data, andencryption type 458 for securing the data, a key derivation algorithmID, a key length, and key derivation information (e.g., a password). Theprocessing module 450 generates a DSN address 454 based on the data ID456. For example, the processing module 450 accesses at least one of adispersed hierarchical index and a dispersed storage network (DSN)directory using the data ID 456 to retrieve the DSN address 454.

The inbound DST processing 82 retrieves at least a decode thresholdnumber of encoded data slices for each set of encoded data slices of thedata from the set of DST execution units 1-n using the DSN address 454.For example, the inbound DST processing 82, for each set of encoded dataslices, generates a set of slice names based on the DSN address 454,issues at least a read threshold number of read slice requests thatincludes a corresponding read threshold number of slice names to the setof DST execution units, and receives at least a decode threshold numberof read slice responses that includes the decode threshold number ofencoded data slices. For each set of encoded data slices, the inboundDST processing 82 decodes the decode threshold number of encoded dataslices to reproduce unsecured data 462.

The processing module 450 generates a first encryption key 460 based onthe secure data request 452. The generating includes performing a keyderivation algorithm using key derivation information of the request inaccordance with the key length of the request to produce the firstencryption key 460. For example, the processing module 450 performs adeterministic function on the password and the data ID 456 to generatethe first encryption key 460. The deterministic function includes one ormore of a hashing function, a hash-based message authentication codefunction, a mask generating function, and a sponge function. Theprocessing module 450 generates a second encryption key 460 based on thesecure data request 452. The generating of the second encryption keyincludes performing another key derivation algorithm using the keyderivation information of the request in accordance with a second keylength of the request to produce the second encryption key 460. Forexample, the processing module 450 performs another deterministicfunction on the password and the data ID 456 in accordance with thesecond key length of the request to produce the second encryption key460.

The encryption module 464 encrypts the data ID 456 using the firstencryption key 460 in accordance with a first encryption algorithm typeof the request to produce an encrypted data ID. The encryption module464 encrypts the encrypted data ID and the unsecured data 462 using thesecond encryption key in accordance with a second encryption algorithmtype of the request to produce an encrypted container. The encryptionmodule issues a secure data response 466 to a requesting entity thatincludes the encrypted container.

FIG. 46B is a flowchart illustrating an example of securely receivingdata. The method includes step 470 where a processing module (e.g., of adistributed storage and task (DST) client module) receives a secure datarequest. The method continues at step 472 where the processing modulegenerates a DSN address based on a data identifier (ID) of the securedata request. The method continues at step 474 where the processingmodule retrieves at least a decode threshold number of encoded dataslices for each set of encoded data slices from a set of storage unitsusing the DSN address.

The method continues at step 476 where the processing module decodeseach decode threshold number of encoded data slices using a dispersedstorage error coding function to reproduce unsecured data. The methodcontinues at step 478 where the processing module generates a firstencryption key based on the secure data request. The generating includesextracting the data ID, a key derivation algorithm, a key length, andkey derivation information including a password from the secure datarequest. The method continues at step 480 where the processing modulegenerates a second encryption key based on the secure data request.

The method continues at step 482 where the processing module encryptsthe data ID using the first encryption key to produce an encrypted dataID. Encryption includes encrypting the data ID utilizing a firstencryption algorithm type of the secure data request. The methodcontinues at step 484 where the processing module encrypts the encrypteddata ID and the unsecured data using the second encryption key toproduce an encrypted container. The encryption includes encrypting theencrypted data ID and the unsecured data utilizing a second encryptionalgorithm type of the secure data request. The second encryptionalgorithm type may be substantially the same as the first encryptionalgorithm type. The method continues at step 486 where the processingmodule issues a secure data response to a requesting entity thatincludes the encrypted container. As such, the secure data response doesnot include a visible data ID.

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network includes the distributed storage and task(DST) client module 34 and a set of DST execution units 1-n of FIG. 1.Alternatively, or in addition to, the network may include two or moresets of DST execution units. In an embodiment, the dispersed storage andtask (DST) processing unit 16 includes at least one module, whenoperable within a computing device, that causes the computing device toperform the following method steps: receiving a data access request;determining an estimated end of life for a plurality of DST executionunits; selecting a subset of the plurality of DST execution units, basedon a threshold number associated with the data access request andfurther based on the estimated end of life for the subset of theplurality of DST execution units; and executing the data access requestvia the subset of the plurality of DST execution units.

The step of determining the estimated end of life for the plurality ofDST execution units can include: obtaining usage information for theplurality of DST execution units to determine an amount of operationtime used for the plurality of DST execution units; and determining theestimated end of life for the plurality of DST execution units based ona difference between an estimated service life and the amount ofoperation time used for the plurality of DST execution units. Theestimated end of life for the plurality of DST execution units can bedetermined based on historical records.

The step of determining the estimated end of life for the plurality ofDST execution units can include: sending a query to the plurality of DSTexecution units; and receiving estimated life data from the plurality ofDST execution units. The step of determining the estimated the estimatedend of life for the plurality of DST execution units can include:sending a query to the plurality of DST execution units; and receivingestimated life data from the plurality of DST execution units. Theestimate life data can include at least one of: usage information, or anestimated amount of operation time to end of life.

Selecting the subset of the plurality of DST execution units can includedetermining ones of the plurality of DST execution units having ahighest amount of time remaining until the estimated end of life.Selecting the subset of the plurality of DST execution units can includeselecting ones of the plurality of DST execution units in proportion toan amount of time remaining until the estimated end of life.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), cause the one or more computing devices to perform any or all ofthe method steps described above.

In an example of operation, the DST client module 34 receives a dataaccess request 500 (e.g., write, read, etc.). The DST client module 34identifies one or more sets of DST execution units that includes the setof DST execution units 1-n, where the one or more sets of DST executionunits are associated with storage of multiple sets of encoded dataslices. Data objects sharing at least one common attribute are encodedusing a dispersed storage error coding function to produce each of themultiple sets of encoded data slices. The common attribute includes atleast one of a common identifier (ID), a common owner, associated with acommon virtual storage vault, associated with multiple generations of acommon data object, and associated with multiple versions of the commondata object.

The DST client module 34 obtains usage information from the one or moresets of DST execution units. For each DST execution unit, the usageinformation includes one or more of an amount of cumulative operationaltime of the DST execution unit, a rated life expectancy amount of timefor the DST execution unit, and estimated amount of operational timeuntil end-of-life of the DST execution unit. The obtaining includes atleast one of initiating a query, receiving usage information,interpreting historical records, and receiving an error message. The DSTclient module 34 determines an estimated amount of time to end-of-lifefor each DST execution unit based on the usage information.

The DST client module 34 determines a threshold number of required DSTexecution units to process the data access request. For example, the DSTclient module 34 indicates a read threshold number of DST executionunits are required when the data access request includes a read request.As another example, the DST client module 34 indicates a write thresholdnumber of DST execution units are required when the data access requestincludes a write request. The DST client module 34 selects the thresholdnumber of DST execution units from a common set of DST execution unitsof the one or more DST execution units based on the threshold number andan associated estimated amount of time to end-of-life in accordance witha selection scheme. For example, the DST client module 34 selects thethreshold number of DST execution units associated with a maximumestimated amount of time to end-of-life when the selection schemeincludes maximizing time to end-of-life.

As another example, the DST client module 34 selects the thresholdnumber of DST execution units in accordance with a pattern where thepattern includes selection in proportion to an associated estimatedamount of time to end-of-life. For instance, if a first DST executionunit is utilizing memory devices that have used 3,000 out of a total of5,000 supported hours of active use and a second DST execution unit isusing memory devices that have used 4,000 of 10,000 hours of active use,the DST client module 34 utilizes a pattern to reach the maximum levelof wear at around the same time for all the drives. In particular, afirst DST execution unit has (5,000-3,000)=2,000 hours left and thesecond DST execution unit has (10,000-4,000)=6,000 hours left. As such,the DST client module 34 sends access requests to the second DSTexecution unit three times as frequently (e.g., 3=6000/2000).

With the threshold number of DST execution units selected, the DSTclient module 34 facilitates processing of the data access request bythe selected threshold number of DST execution units. For example, theDST client module 34 generates DSN addressing information based on theselected set of DST execution units that includes the threshold numberof DST execution units. Next the DST client module 34 issues sliceaccess requests to the selected threshold number of DST execution unitsusing the DSN addressing information. The DST client module 34 receivesslice access responses from at least some of the selected thresholdnumber of DST execution units. The DST client module 34 issues a dataaccess response 502 to a requesting entity based on the received sliceaccess responses (e.g., write status, recovered data).

FIG. 47B is a flowchart illustrating an example of balancing storageunit utilization. The method includes step 510 where a processing module(e.g., of a distributed storage and task (DST) client module) receives adata access request. The method continues at step 512 where theprocessing module identifies one or more sets of storage unitsassociated with the data access requests. For example, the processingmodule utilizes a data identifier of the data access request to access adispersed storage network (DSN) directory to retrieve a DSN address.Next, the processing module identifies the one or more sets of storageunits based on the DSN address, where each set is associated with aportion of the DSN address (e.g., a generation number).

The method continues at step 514 where the processing module obtainsusage information for each storage unit of the one or more sets ofstorage units. The method continues at step 516 where the processingmodule determines an estimated amount of time to end-of-life for eachstorage unit. As a specific example, the processing module obtainsestimated service life and calculates a difference between estimatedservice life and an amount of operational time utilized so far toproduce the estimated amount of time to end-of-life. As another specificexample, the processing module receives the estimated amount of time toend-of-life from the storage unit. As yet another specific example, theprocessing module estimates the estimated amount of time to end-of-lifefor the storage unit based on historical records.

The method continues at step 518 where the processing module determinesa threshold number of required storage units for the data accessrequest. As a specific example, the processing module accesses registryinformation for a vault associated with the DSN address to identifydispersal parameters that includes a write threshold and a readthreshold. The processing module selects the write threshold as thethreshold number when the data access request includes a write requestand selects the read threshold as the threshold number when the dataaccess request includes a read request.

The method continues at step 520 where the processing module selects athreshold number of storage units from a common set of storage unitsbased on the threshold number and the estimated amount of time toend-of-life in accordance with a selection scheme. As a specificexample, the processing module selects the threshold number of storageunits from a first set of storage units where each of the selectedthreshold number of storage units is associated with an estimated amountof time to end-of-life that is greater than estimated amount of time toend-of-life for other storage units. The method continues at step 522where the processing module executes the data access request using theselected threshold number of storage units. As a specific example, theprocessing module modifies the DSN address based on the selectedthreshold number of storage units (e.g., in accordance with anassociated generation number) to produce a modified DSN address andissues a threshold number of slice access requests to the selectedthreshold number of storage units utilizing the modified DSN address.The processing module receives slice access responses from at least someof the selected threshold number of storage units. Having received asufficient number of slice access responses, the processing moduleissues a data access response to the requesting entity based on thereceived slice access responses.

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network includes the distributed storage and task(DST) client module 34 and a set of DST execution units 1-n of FIG. 1.In an example of operation, at a time t0, the DST client module 34receives a data access request 530 (e.g., write, read, etc.). The DSTclient module 34 determines an access performance level of one or moreprevious data access requests. The access performance level includes atleast one of a rolling average response time between receiving theprevious data access request and responding with a previous data accessresponse (e.g., 10 msec) and a standard deviation of the response time(e.g., 95% of response times are within 8-12 msec). For instance, aresponse time for the present data access request includes a differencebetween outputting of a corresponding data access response at time t1and the receipt of the data access request at time t0. The DST clientmodule 34 performs the determining based on one or more of initiating aquery, receiving a query response, interpreting historical record, andperforming a test.

Having determined the access performance level, the DST client module 34schedules processing of the data access request in accordance with theaccess performance level and a desired access performance level. Thescheduling includes identifying a subsequent time frame to initiateprocessing of the data access request. As a specific example, the DSTclient module schedules the processing of the data access request withthe desired access performance levels to include no more than 99% of thecircle response times are to be longer than 120 ms. Such scheduling mayconstrain throughput of data access request processing in favor ofimproved access performance.

When the scheduling indicates that the data access is to be executed,the DST client module 34 facilitates execution of the data accessrequest 530. For example, the DST client module 34 issues a set of sliceaccess requests 1-n to the set of DST execution units, receives sliceaccess responses of a set of slice access responses 1-n, and issues thedata access response to a requesting entity at time t1 based on thereceived slice access responses. When the DST client module 34 detectsthat the access performance level does not achieve the desired accessperformance level for a given timeframe (e.g., a performance differenceis outside of a performance difference threshold level), the DST clientmodule 34 implements an alternate throughput scheme based on theperformance difference. For example, the DST client module implementsone or more throughput reduction procedures when the access performancelevel is less than the desired access performance level (e.g., responsetime greater than desired, standard deviation response time greater thandesired). The one or more throughput reduction procedures includesrejecting a future data access request, redirecting at least one dataaccess request to another DST client module, and delaying the issuing ofthe data access response 532 to the requesting entity.

FIG. 48B is a flowchart illustrating an example of adjusting data accessthroughput, which include similar steps to FIG. 47B. The method beginswith the step 540 of FIG. 47B where a processing module (e.g., of adistributed storage and task (DST) client module) receives a data accessrequest. The method continues at step 542 where the processing moduledetermines access performance level for previous data access requests.The method continues at step 544 where the processing module determinesa desired access performance level. The determining includes at leastone of utilizing a predetermination, receiving a user input, obtaining arequesting entity input, and utilizing an access performance levelassociated with a previous data access request.

The method continues at step 546 where the processing module schedulesprocessing of the data access request in accordance with the accessperformance level and the desired access performance level to produce anexecution schedule. The method continues at step 548 where theprocessing module executes the data access request in accordance withthe execution schedule. The method continues at step 550 where theprocessing module determines an updated access performance level forfurther data access requests. As a specific example, the processingmodule determines the updated access performance level for a widerselection of data access requests. As another specific example, theprocessing module determines the updated access performance level for anarrower selection of data access requests. As yet another specificexample, the processing module determines the updated access performancelevel for previous data access requests including a data access request.

When the updated access performance level compares unfavorably to thedesired access performance level, the method continues at step 552 wherethe processing module implements an alternate throughput scheme. As aspecific example, the processing module indicates that the updatedaccess performance level compares unfavorably to the desired accessperformance level when the updated access performance level is less thanthe desired access performance level. The implementing includesdetermining whether to increase or decrease throughput of data accessrequests being processed into data access responses. As a specificexample, the processing module determines to increase throughput (e.g.,to schedule more data access requests within a given timeframe) when theupdated access performance level is greater than the desired accessperformance level by a performance difference threshold level. Asanother specific example, the processing module determines to decreasethroughput (e.g., to schedule fewer data access requests within thegiven timeframe) when the updated access performance level is less thanthe desired access performance level by the performance differencethreshold level.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that stepspresented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that steps presented may be performed multiple times and/or maybe succeeded by other activities not specifically shown. Further, whilea flow diagram indicates a particular ordering of steps, other orderingsare likewise possible provided that the principles of causality aremaintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage and task(DST) network, the method comprises: receiving an access request;determining an estimated processing load associated with the accessrequest; selecting a processing resource based on the estimatedprocessing load; determining a coordinated execution schedule for aplurality of DST execution units; and assigning the access request tothe processing resource in accordance with the coordinated executionschedule.
 2. The method of claim 1 further comprising: detecting anexecution deviation in the coordinated execution schedule; and updatingthe coordinated execution schedule in response to the executiondeviation.
 3. The method of claim 1 wherein the estimated processingload is determined based on at least one of: an access typecorresponding to the access request, or a quantity of data slicesassociated with the access request.
 4. The method of claim 1 wherein theprocessing resource is selected from a plurality of processingresources, based on a capability of the processing resource.
 5. Themethod of claim 1 wherein the coordinated execution schedule isdetermined based on at least one of: an execution status associated withone or more current access requests, or a number of access requests inqueue.
 6. The method of claim 1 wherein the coordinated executionschedule is determined to coordinate commencement of the access requestacross at least a subset of the plurality of DST execution units.
 7. Themethod of claim 1 wherein the coordinated execution schedule isdetermined to coordinate commencement of the access request across atleast a subset of the plurality of DST execution units based on anestimated completion time of one or more prior access requests.
 8. Adispersed storage and task (DST) processing unit comprises: at least onemodule, when operable within a computing device, that causes thecomputing device to: receive an access request; determine an estimatedprocessing load associated with the access request; select a processingresource based on the estimated processing load; determine a coordinatedexecution schedule for a plurality of DST execution units; and assignthe access request to the processing resource in accordance with thecoordinated execution schedule.
 9. The DST processing unit of claim 8wherein the at least one module, when operable within the computingdevice, further causes the computing device to: detect an executiondeviation in the coordinated execution schedule; and update thecoordinated execution schedule in response to the execution deviation.10. The DST processing unit of claim 8 wherein the estimated processingload is determined based on at least one of: an access typecorresponding to the access request, or a quantity of data slicesassociated with the access request.
 11. The DST processing unit of claim8 wherein the processing resource is selected from a plurality ofprocessing resources, based on a capability of the processing resource.12. The DST processing unit of claim 8 wherein the coordinated executionschedule is determined based on at least one of: an execution statusassociated with one or more current access requests, or a number ofaccess requests in queue.
 13. The DST processing unit of claim 8 whereinthe coordinated execution schedule is determined to coordinatecommencement of the access request across at least a subset of theplurality of DST execution units.
 14. The DST processing unit of claim 8wherein the coordinated execution schedule is determined to coordinatecommencement of the access request across at least a subset of theplurality of DST execution units based on an estimated completion timeof one or more prior access requests.
 15. A computer readable storagemedium comprises: at least one memory section that stores operationalinstructions that, when executed by one or more processing modules ofone or more computing devices of a dispersed storage and task (DST)network, causes the one or more computing devices to: receive an accessrequest; determine an estimated processing load associated with theaccess request; select a processing resource based on the estimatedprocessing load; determine a coordinated execution schedule for aplurality of DST execution units; and assign the access request to theprocessing resource in accordance with the coordinated executionschedule.
 16. The DST processing unit of claim 15 wherein theoperational instructions, when executed by the one or more processingmodules of the one or more computing devices of the dispersed storagenetwork (DSN), further causes the one or more computing devices to:detect an execution deviation in the coordinated execution schedule; andupdate the coordinated execution schedule in response to the executiondeviation.
 17. The computer readable storage medium of claim 15 whereinthe estimated processing load is determined based on at least one of: anaccess type corresponding to the access request, or a quantity of dataslices associated with the access request.
 18. The computer readablestorage medium of claim 15 wherein the coordinated execution schedule isdetermined based on at least one of: an execution status associated withone or more current access requests, or a number of access requests inqueue.
 19. The computer readable storage medium of claim 15 wherein thecoordinated execution schedule is determined to coordinate commencementof the access request across at least a subset of the plurality of DSTexecution units.
 20. The computer readable storage medium of claim 15wherein the coordinated execution schedule is determined to coordinatecommencement of the access request across at least a subset of theplurality of DST execution units based on an estimated completion timeof one or more prior access requests.